TITLE Assessment of the application of multibeam echosounder

TITLE

Assessment of the application of multibeam echosounder technologies to UK marine habitat classification systems. SUPERVISOR(S)

Dr. Gay Mitchelson-Jacob, Dr. Ronan Roche, Dr. Jim Bennell COLLABORATION/CASE PARTNERS

Is it expected that this project would lead to collaborations with marine ecological survey companies such as Marine Ecological Solutions Ltd., based in Menai Bridge. BACKGROUND/CONTEXT OF PROJECT

Multibeam echosounder (MBES) systems are widely recognised as an effective tool for seafloor mapping, but the quantitative characterisation of MBES data and its application to ecologically relevant classification systems is less developed. Whilst the data availability and spatial resolution of MBES systems are advancing, the computing power to analyse large multivariate physical and ecological survey datasets is also increasingly available. The acoustic backscatter data captured by MBES has application in mapping of surficial sediments, and methods have been developed to objectively classify backscatter information into acoustically similar regions (Brown et al., 2011). Ground-truthing of results has shown variable ability of such systems to correctly identify sediment characteristics and indicates that improvements can be made in classification techniques. Physical gradients in particle size are correlated with biological community composition, and an emerging body of research is investigating the ability of acoustic backscatter data to identify marine biological assemblages. Considerable variability has been shown in the strength of correlations observed between acoustic signal-based classification and ground truth video data. However, high levels of correlation are observed for specific benthic habitats such as Sabellaria reef, seagrass meadows and mussel beds (e.g. van Rein et al., 2011). Questions remain as to the degree of detail with which acoustic backscatter data can be applied to ecological mapping and the extent to which its inclusion in multi-method classification techniques is useful. At present, many elements of assigning biotopes to an area based on ecological survey results are heavily based upon expert judgment. This has the disadvantage of being a subjective methodology, such that the final biotope choice may be difficult to defend. There is an opportunity for developing statistical tools to support the decision making process and to incorporate additional types of data such as acoustic backscatter for achieving more robust objective outcomes in the biotoping process.

AIMS AND OBJECTIVES

Aims: 1. To investigate the ability of MBES data to contribute to biotope mapping, by comparing classification based on acoustic backscatter data with ground-truthing methods. 2. To develop novel techniques to support the decision-making process in the marine biotoping process. Objectives: 1. To carry out ship-based surveys of marine habitat incorporating MBES data acquisition, video (sledge or drop-down) and sediment grab-sampling techniques. 2. To examine methods for refining systems of marine habitat classification based on acoustic backscatter data. 3. To rigorously compare results obtained with video and sedimentological data. 4. To analyze the existing database of acoustic backscatter data, in order to test the application of classification methods on a range of sedimentary environments. 5. To develop techniques for improving the marine biotoping classification process, by testing the potential contribution of biological abundance measurements, and acoustic backscatter data. MATERIALS/METHODS/TRAINING ELEMENT

Materials and Methods: This project would expand the application of the MBES systems available on board the R/V Prince Madog and the Macoma. Considerable amounts of acoustic backscatter data have been collected during cruises, but the majority has not yet been analysed. In addition to working with this database of existing data, it is expected that this project would focus on collection of new data from a suitable site as a basis for comparative analysis. Training methods would include: 1. Training in ship-based collection of sediment grab samples, video surveys, and multibeam data acquisition. 2. Training in MBES data processing methods using the PDS 2000 software. 3. Training in lab-based sedimentological analysis, video survey analysis and GIS mapping techniques. 4. Development of a familiarity with the UK MNCR biotoping classification system, as well as the EU EUNIS classification system. COSTS

As this project is related to SEACAMS R & D project(s), most of the project costs will be met through SEACAMS.

Prince Madog cruise time. It is expected that the PhD would entail participation in 2 SEACAMS cruises of approximately five days duration aboard the R/V Prince Madog. Macoma boat time. This project may additionally require 2 weeks of SEACAMS Macoma time for MBES data collection, and collection of sediment and drop-down video data for ground truthing. Consumables associated with in situ sampling will be met through SEACAMS. There are software requirements to enable processing of MBES acoustic backscatter data. Some classification may be done using the PDS 2000 and Fledermaus Geocoder software which SOS has, however software such as QTC Swathview would considerably expand the ability to process and classify acoustic backscatter data. A quote has been received for QTC Swathview which is ~£12,000. References: Brown, Craig J.; Todd, Brian J.; Kostylev, Vladimir E. (2011). Image-based classification of multibeam sonar backscatter data for ojbective surficial sediment mapping of Georges Bank, Canada. CONTINENTAL SHELF RESEARCH Volume: 31 Issue: 2 Special Issue: SI Supplement: S Pages: S110-S119 DOI: 10.1016/j.csr.2010.02. van Rein, H.; Brown, C. J.; Quinn, R. (2011) An evaluation of acoustic seabed classification techniques for marine biotope monitoring over broad-scales (>1 km2) and meso-sclaes (10 m2 -1 km2). ESTUARINE COASTAL AND SHELF SCIENCE Volume: 93 Issue: 4 Pages: 336-349 DOI: 10.1016/j.ecss.2011.04.011